@article{ref1,
title="Mobile edge computing for the internet of vehicles: offloading framework and job scheduling",
journal="IEEE vehicular technology magazine",
year="2019",
author="Feng, Jingyun and Liu, Zhi and Wu, Celimuge and Ji, Yusheng",
volume="14",
number="1",
pages="28-36",
abstract="As an enabling technology for the Internet of Vehicles (IoV), mobile edge computing (MEC) provides potential solutions for sharing the computation capabilities among vehicles, in addition to other accessible resources. In this article, we first introduce a distributed vehicular edge computing solution named the autonomous vehicular edge (AVE), which makes it possible to share neighboring vehicles' available resources via vehicle-tovehicle (V2V) communications. We then extend this concept to a more general online solution called the hybrid vehicular edge cloud (HVC), which enables the efficient sharing of all accessible computing resources, including roadside units (RSUs) and the cloud, by using multiaccess networks. We also demonstrate the impact of these two decentralized edge computing solutions on the task execution performance. Finally, we discuss several open problems and future research directions.<p /> <p>Language: en</p>",
language="en",
issn="1556-6072",
doi="10.1109/MVT.2018.2879647",
url="http://dx.doi.org/10.1109/MVT.2018.2879647"
}